Triple
T10290402
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Issoudun |
E241346
|
entity |
| Predicate | hasTwinTown |
P919
|
FINISHED |
| Object | Poggibonsi |
E848288
|
NE FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Poggibonsi | Statement: [Issoudun, hasTwinTown, Poggibonsi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Poggibonsi Context triple: [Issoudun, hasTwinTown, Poggibonsi]
-
A.
Poggibonsi
chosen
Poggibonsi is a Tuscan town in central Italy known for its medieval history, archaeological sites, and position along historic pilgrimage and trade routes between Florence and Siena.
-
B.
Montemurlo
Montemurlo is a municipality in the Tuscany region of central Italy, known for its industrial activity and proximity to the city of Prato.
-
C.
Bagnacavallo
Bagnacavallo is a historic town in Italy’s Emilia-Romagna region, known for its well-preserved medieval center and traditional rural culture.
-
D.
Bibbiena
Bibbiena is a historic town and municipality in Tuscany, central Italy, known for its medieval architecture and scenic setting in the Casentino valley.
-
E.
Poggio San Lorenzo
Poggio San Lorenzo is a small Italian municipality in the Lazio region, known for its rural setting and historical hilltop village character.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d381aaafc08190af475ef58dc16aba |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d2d192288190a64c27a4f26b71fc |
completed | April 7, 2026, 9:48 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d794c79ae88190b80c805f7671e264 |
completed | April 9, 2026, noon |
Created at: April 6, 2026, 11:41 a.m.